#基本数据分析
import pandas as pd
import numpy as np
#可视化

import matplotlib.pyplot as plt
import seaborn as sns
#模型， 数据处理，模型融合 相关方法。
from sklearn.preprocessing import LabelEncoder
from sklearn.model_selection import train_test_split
from sklearn.linear_model import LogisticRegression
from sklearn.svm import SVC, LinearSVC
from sklearn.ensemble import RandomForestClassifier
from sklearn.neighbors import KNeighborsClassifier
from sklearn.naive_bayes import GaussianNB
from sklearn.linear_model import Perceptron
from sklearn.linear_model import SGDClassifier
from sklearn.tree import DecisionTreeClassifier

from sklearn.metrics import precision_score
from sklearn.ensemble import GradientBoostingClassifier
from sklearn.model_selection import GridSearchCV, cross_val_score, StratifiedKFold, learning_curve
import warnings
warnings.filterwarnings('ignore')


train_df=pd.read_csv('./Project/dataset/titanic/train.csv') #训练集
test_df=pd.read_csv('./Project/dataset/titanic/test.csv')  #测试集
predict_df=pd.read_csv('./Project/dataset/titanic/gender_submission.csv')  #测试集

print("\n\n--------------------------训练集 train 的内容：\n\n", train_df)
print("\n\n--------------------------测试集 test  的内容：\n\n", test_df)
print("\n\n--------------------------提交结果predict模板: \n\n", predict_df)
